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ORIGINAL RESEARCH article
Front. Energy Res.
Sec. Smart Grids
Volume 12 - 2024 |
doi: 10.3389/fenrg.2024.1421555
A New Dynamic State Estimation Method for Distribution Network Based modified SVSF Considering Photovoltaic Power Prediction
Provisionally accepted
Huiqiang Zhi
1*
Xiao Chang
1*
Jinhao Wang
1*
Rui Mao
1*
Rui Fan
1*
Tengxin Wang
1*
Jinge Song
1*
Guisheng Xiao
2- 1 State Grid Shanxi Electric Power Company Electric Power Research Institute, Taiyuan, Shanxi Province, China
- 2 Shanghai University of Electric Power, Shanghai, China
The fluctuations brought by the renewable energy access to the distribution network make it difficult to accurately describe the state space model of the distribution network's dynamic process, which is the basis of the existing dynamic state estimation methods such as the Kalman filter. The inaccurate state space model directly causes an error of dynamic state estimation results. This paper proposed a new dynamic state estimation method which can mitigates the impact of renewable energy fluctuation by considering PV power prediction in establishing distribution network state space model. The modified smooth variable structure filter can improve the problem of state space model of the distribution network with a large amount of renewable energy and inherently improve the accuracy of dynamic state estimation. The case study and evaluations are carried out based on MATLAB simulation. The results prove that the smooth variable structure filter with photovoltaic power prediction has a better dynamic state estimation effect under the fluctuation of the distribution network compared with the existing Kalman filter.
Keywords: Dynamic state estimation, Smooth variable structure filter, Distribution networks, Photovoltaic power prediction, Voltage magnitude, Voltage phase angle
Received: 22 Apr 2024; Accepted: 18 Jul 2024.
Copyright: © 2024 Zhi, Chang, Wang, Mao, Fan, Wang, Song and Xiao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Huiqiang Zhi, State Grid Shanxi Electric Power Company Electric Power Research Institute, Taiyuan, Shanxi Province, China
Xiao Chang, State Grid Shanxi Electric Power Company Electric Power Research Institute, Taiyuan, Shanxi Province, China
Jinhao Wang, State Grid Shanxi Electric Power Company Electric Power Research Institute, Taiyuan, Shanxi Province, China
Rui Mao, State Grid Shanxi Electric Power Company Electric Power Research Institute, Taiyuan, Shanxi Province, China
Rui Fan, State Grid Shanxi Electric Power Company Electric Power Research Institute, Taiyuan, Shanxi Province, China
Tengxin Wang, State Grid Shanxi Electric Power Company Electric Power Research Institute, Taiyuan, Shanxi Province, China
Jinge Song, State Grid Shanxi Electric Power Company Electric Power Research Institute, Taiyuan, Shanxi Province, China
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